Population structure promotes the evolution of costly sex in artificial gene networks

We build on previous observations that Hill–Robertson interference generates an advantage of sex that, in structured populations, can be large enough to explain the evolutionary maintenance of costly sex. We employed a gene network model that explicitly incorporates interactions between genes. Mutations in the gene networks have variable effects that depend on the genetic background in which they appear. Consequently, our simulations include two costs of sex—recombination and migration loads—that were missing from previous studies of the evolution of costly sex. Our results suggest a critical role for population structure that lies in its ability to align the long- and short-term advantages of sex. We show that the addition of population structure favored the evolution of sex by disproportionately decreasing the equilibrium mean fitness of asexual populations, primarily by increasing the strength of Muller's Ratchet. Population structure also increased the ability of the short-term advantage of sex to counter the primary limit to the evolution of sex in the gene network model—recombination load. On the other hand, highly structured populations experienced migration load in the form of Dobzhansky–Muller incompatibilities, decreasing the effective rate of migration between demes and, consequently, accelerating the accumulation of drift load in the sexual populations

A generative bias towards average complexity in artificial cell lineages

The evolution of life on earth has been characterized by generalized long-term increases in phenotypic complexity. Although natural selection is a plausible cause for these trends, one alternative hypothesis generative bias-has been proposed repeatedly based on theoretical considerations. Here, we introduce a computational model of a developmental system and use it to test the hypothesis that long-term increasing trends in phenotypic complexity are caused by a generative bias towards greater complexity. We use our model to generate random organisms with different levels of phenotypic complexity and analyse the distributions of mutational effects on complexity. We show that highly complex organisms are easy to generate but there are trade-offs between different measures of complexity. We also find that only the simplest possible phenotypes show a generative bias towards higher complexity, whereas phenotypes with high complexity display a generative bias towards lower complexity. These results suggest that generative biases alone are not sufficient to explain long-term evolutionary increases in phenotypic complexity. Rather, our finding of a generative bias towards average complexity argues for a critical role of selective biases in driving increases in phenotypic complexity and in maintaining high complexity once it has evolved

How Common and How Large are Cost Overruns in Transport Infrastructure Projects?

Despite the hundreds of billions of dollars being spent on infrastructure development — from roads, rail and airports to energy extraction and power networks to the Internet — surprisingly little reliable knowledge exists about the performance of these investments in terms of actual costs, benefits and risks. This paper presents results from the first statistically significant study of cost performance in transport infrastructure projects. The sample used is the largest of its kind, covering 258 projects in 20 nations worth approximately US$90 billion (constant 1995 prices). The paper shows with overwhelming statistical significance that in terms of costs transport infrastructure projects do not perform as promised. The conclusion is tested for different project types, different geographical regions and different historical periods. Substantial cost escalation is the rule rather than the exception. For rail, average cost escalation is 45% (SD=38), for fixed links (tunnels and bridges) it is 34% (62) and for roads 20% (30). Cost escalation appears a global phenomenon, existing across 20 nations on five continents. Cost estimates have not improved and cost escalation not decreased over the past 70 years. Cost estimates used in decision-making for transport infrastructure development are highly, systematically and significantly misleading. Large cost escalations combined with large standard deviations translate into large financial risks. However, such risks are typically ignored or underplayed in decision-making, to the detriment of social and economic welfare.

Why does a grasshopper have fewer, larger offspring at its range limits?

Analysis of size of offspring reared through three laboratory generations from populations of the field grasshopper Chorthippus brunneus from 27 sites around the British Isles showed that offspring were larger towards the cooler-wetter conditions in the western and northern limits of the range. This variation had a significant genetic component. There was a trade-off between clutch size and offspring size between and within populations. Under favourable thermal and feeding conditions maternal fitness was optimal when individuals produced the largest clutches of the smallest eggs, but under poor conditions maternal fitness was optimal when individuals produced small clutches of very large offspring. Calculation of geometric mean fitness over time indicated that having larger offspring near to the edge of the range could be advantageous as a conservative risk-spreading strategy. As well as geographic variation in egg size, significant environment-genotype interactions in egg size in relation to temperature were observed